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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| AugMax: Adversarial Composition of Random Augmentations for Robust Training |
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| Haotao Wang, Chaowei Xiao, Jean Kossaifi |
| 2021 |
| arxiv 2110.13771 |
| Probabilistic Language-Image Pre-Training | Sanghyuk Chun, Wonjae Kim, Song Park | 2024 | arxiv 2410.18857 |
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| CoSwin: Convolution Enhanced Hierarchical Shifted Window Attention For Small-Scale Vision | Puskal Khadka, Rodrigue Rizk, Longwei Wang | 2025 | arxiv 2509.08959 |
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| DW-GAN: A Discrete Wavelet Transform GAN for NonHomogeneous Dehazing | Minghan Fu, Huan Liu, Yankun Yu | 2021 | arxiv 2104.08911 |
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| Enhancing Contrastive Learning with Efficient Combinatorial Positive Pairing | Jaeill Kim, Duhun Hwang, Eunjung Lee | 2024 | arxiv 2401.05730 |
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| How does topology influence gradient propagation and model performance of deep networks with DenseNet-type skip connections? | Kartikeya Bhardwaj, Guihong Li, Radu Marculescu | 2019 | arxiv 1910.00780 |
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| How to Train Vision Transformer on Small-scale Datasets? | Hanan Gani, Muzammal Naseer, Mohammad Yaqub | 2022 | arxiv 2210.07240 |
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| Separable Self-attention for Mobile Vision Transformers | Sachin Mehta, Mohammad Rastegari | 2022 | arxiv 2206.02680 |
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| Parameter Prediction for Unseen Deep Architectures | Boris Knyazev, Michal Drozdzal, Graham W. Taylor | 2021 | arxiv 2110.13100 |
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| ScaleCert: Scalable Certified Defense against Adversarial Patches with Sparse Superficial Layers | Husheng Han, Kaidi Xu, Xing Hu | 2021 | arxiv 2110.14120 |
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